Method and Apparatus Pertaining to Radiation-Treatment Plan Optimization

ABSTRACT

A radiation-treatment plan that comprises a plurality of dose-delivery fractions can be optimized by using fraction dose objectives and at least one other, different dose objective. This use of fraction dose objectives can comprise accumulating doses delivered in previous dose-delivery fractions. The other, different dose objective can comprise a remaining total dose objective, a predictive dose objective, or some other dose objective of choice. An existing radiation-treatment plan having a corresponding resultant quality and that is defined, at least in part, by at least one delivery parameter can be re-optimized by specifying at least one constraint as regards that delivery parameter as a function, at least in part, of that resultant quality and then applying that constraint when re-optimizing the existing radiation-treatment plan.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of prior U.S. patent application Ser.No. 15/085,494, filed Mar. 30, 2016, which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

This invention relates generally to the optimization ofradiation-therapy treatment plans.

BACKGROUND

The use of radiation to treat medical conditions comprises a known areaof prior art endeavor. For example, radiation therapy comprises animportant component of many treatment plans for reducing or eliminatingunwanted tumors. Unfortunately, applied radiation does not inherentlydiscriminate between unwanted materials and adjacent tissues, organs, orthe like that are desired or even critical to continued survival of thepatient. As a result, radiation is ordinarily applied in a carefullyadministered manner to at least attempt to restrict the radiation to agiven target volume.

Treatment plans typically serve to specify any number of operatingparameters as pertain to the administration of such treatment withrespect to a given patient. For example, many treatment plans comprise aseries of delivery fractions that provide for exposing the target volumeto possibly varying dosages of radiation from a number of differentdirections. Arc therapy, for example, comprises one such approach.

Such treatment plans are often optimized prior to use. (As used herein,“optimization” will be understood to refer to improving a candidatetreatment plan without necessarily ensuring that the optimized resultis, in fact, the singular best solution.) Though important to the use oftreatment plans, typical optimization processes are computationallyintensive. This, in turn, can require the use of expensive processingplatforms and/or a considerable amount of processing time. Such burdens,however, can lead to unwanted costs and/or delay for the serviceprovider and/or the patient.

Existing approaches in these regards, while useful, are not necessarilybest suited for all potential application settings.

BRIEF DESCRIPTION OF THE DRAWINGS

The above needs are at least partially met through provision of themethod and apparatus pertaining to radiation-treatment plan optimizationdescribed in the following detailed description, particularly whenstudied in conjunction with the drawings, wherein:

FIG. 1 comprises a flow diagram as configured in accordance with variousembodiments of the invention;

FIG. 2 comprises a flow diagram as configured in accordance with variousembodiments of the invention;

FIG. 3 comprises a perspective, schematic view as configured inaccordance with various embodiments of the invention; and

FIG. 4 comprises a block diagram as configured in accordance withvarious embodiments of the invention.

Elements in the figures are illustrated for simplicity and clarity andhave not necessarily been drawn to scale. For example, the dimensionsand/or relative positioning of some of the elements in the figures maybe exaggerated relative to other elements to help to improveunderstanding of various embodiments of the present invention. Also,common but well-understood elements that are useful or necessary in acommercially feasible embodiment are often not depicted in order tofacilitate a less obstructed view of these various embodiments of thepresent invention. Certain actions and/or steps may be described ordepicted in a particular order of occurrence while those skilled in theart will understand that such specificity with respect to sequence isnot actually required. The terms and expressions used herein have theordinary technical meaning as is accorded to such terms and expressionsby persons skilled in the technical field as set forth above exceptwhere different specific meanings have otherwise been set forth herein.

DETAILED DESCRIPTION

Generally speaking, pursuant to various ones of these embodiments, aradiation-treatment plan that comprises a plurality of dose-deliveryfractions is optimized, at least in part, by optimizing that plan usingfraction dose objectives and at least one other, different doseobjective. By one approach, this use of fraction dose objectives cancomprise, at least in part, accumulating doses delivered in previousdose-delivery fractions. By one approach, such accumulation can compriseproducing a mapping from fraction geometry to reference geometry andthen using that mapping to accumulate the doses in the referencegeometry. By another approach, the aforementioned fraction doseobjectives can comprise, at least in part, dose-volume histogramobjectives. The other, different dose objective can comprise, forexample, a remaining total dose objective, a predictive dose objective,or some other dose objective of choice.

Also pursuant to various ones of these embodiments, an existingradiation-treatment plan having a corresponding resultant quality andthat is defined, at least in part, by at least one delivery parametercan be re-optimized by specifying at least one constraint as regardsthat delivery parameter as a function, at least in part, of thatresultant quality and then applying that constraint when re-optimizingthe existing radiation-treatment plan. Using this approach can serve toat least substantially maintain the resultant quality of there-optimized plan while nevertheless permitting changes to the existingradiation-treatment plan.

In such a case, and as one example in these regards, the aforementioneddelivery parameter can pertain to fluence. By another approach, in lieuof the foregoing or in combination therewith, the aforementioneddelivery parameter can pertain to one or more mechanical settings of thecorresponding radiation-delivery apparatus. This can comprise, forexample, mechanical settings as regards multi-leaf collimator leafposition settings. Other examples include, but are not limited to,collimator angle and/or position, patient support positions/movement,and dose-administration rates.

So configured, radiation-treatment optimization plans can be formedand/or re-optimized in ways that can yield, at least under someoperating circumstances, superior results and/or useful results thatrequire less processing time and/or computational capacity as comparedto other approaches in these regards. These teachings are readilyapplied in conjunction with existing radiation-treatment platforms andcan serve to leverage the continued utility of those platforms. Theseapproaches are also highly scalable and can be employed to good purposein a wide variety of application settings and for any number ofdiffering radiation-treatment modalities and methodologies.

These and other benefits may become clearer upon making a thoroughreview and study of the following detailed description. Referring now tothe drawings, and in particular to FIG. 1, an illustrative process 100that is compatible with many of these teachings will now be presented.This process 100 can be carried out by an appropriately configuredcontrol circuit as described below.

This process 100 can be applied when optimizing a radiation-treatmentplan comprised of a plurality of dose-delivery fractions. Many radiationtreatments are parsed into treatment fractions to accommodate the factthat, for example, patient geometry may change over the course oftreatment (as, for example, the position of the radiation sourcerelative to the patient changes during the treatment session and/orbetween treatment sessions). By way of illustration, the size, shape, orposition of a tumor to be treated or nearby critical organs may change.

A dose-delivery fraction comprises the treatment-parameter settings thatare utilized during a fractional portion of a given treatment session.Examples include, but are not limited to, settings regarding thepatient's position, the position of the radiation source with respect tothe patient, dose intensity and/duration, collimator position,orientation, and configuration, and so forth.

This process 100 provides, in part, for the step 101 of optimizing sucha radiation-treatment plan using both fraction dose objectives as wellas at least one other different dose objective.

This can comprise, for example, limiting dose distribution for eachorgan/structure within a single fraction to no more than some maximumamount. By way of illustration, this can comprise specifying that thepatient's spine should not receive more than a specified amount ofradiation in any fraction regardless of how much radiation is receivedin another delivery fraction. Such a fractional-based limit can reflecta concern that a given organ/structure may not be able to satisfactorilyrecover from an excessive fractional dose even when the total treatmentdosage is less than some other maximum value.

As another illustrative example, this can comprise ensuring at least aminimal dosage during any given delivery fraction in order to betterensure a desired biological response.

This process 100 will accommodate a variety of practices in theseregards as regards the use of fraction dose objectives. By one approach,for example, this can comprise accumulating doses delivered in previousdose-delivery fractions. This can comprise, by way of example andwithout intending any limitations in these regards, for producing amapping from fraction geometry to reference geometry and then using thatmapping to accumulate doses in the reference geometry. This referencegeometry can refer, for example, to a pre-treatment computed tomography(CT) image of the patient. Generally speaking the reference geometry canrefer to any patient image (or images) that clearly represents theorgans/volumes of interest. Images acquired during treatment may offerless coverage or clarity than such a reference image, but in some casesmay be sufficient to support modeling the radiation dose distributionfor, say, a particular subset of treatment fractions. If desired,producing this mapping can comprise, for example, determining adeformable image registration between a patient image and a referencepatient image.

As another illustrative example, the fraction dose objectives cancomprise, at least in part, dose-volume histogram (DVH) objectives.DVH's typical represent three-dimensional dose distributions in agraphical two-dimensional format (the three-dimensional dosedistributions being created, for example, in a computerizedradiation-treatment planning system based on a three-dimensionalreconstruction of an X-ray computed tomography scan and study. The“volume” referred to in DVH analysis can be, for example, theradiation-treatment target, a healthy organ located near such a target,an arbitrary structure, and so forth.

DVH's are often visualized in either of two ways: as differential DVH'sor as cumulative DVH's. With differential DVH's column height for agiven dose bin corresponds to the volume of the structure that receivesthat dose. Bin doses typically extend along the horizontal axis whilestructure volumes (either percent or absolute volumes) extend along thevertical axis.

A cumulative DVH is typically plotted with bin doses along thehorizontal axis but has a column height for the first bin thatrepresents the volume of structure(s) that receive greater than or equalto that dose. The column height of the second bin then represents thevolume of structure(s) that receive greater than or equal to that dose,and so forth. With high granularity a cumulative DVH often appears as asmooth line graph. For many application settings cumulative DVH's arepreferred over differential DVH's but this process 100 can accommodateeither approach.

As specified above, this step 101 provides for optimizing aradiation-treatment plan using both fraction dose objectives as well asat least one other different dose objective. This other, different doseobjective can vary with the needs of a given application setting. As oneuseful example in these regards, this other, different dose objectivecan comprise a remaining total-dose objective. This comprises, for agiven delivery fraction as comprises a part of a givenradiation-treatment plan being optimized, some objective total-dose goalor limit less accumulated doses administered by earlier deliveryfractions. This can be represented as:

TD_(R)(n)=TD_(G)−(FD(1)+ . . . +FD(n−1))

where TD_(R)(n) refers to the total dose remaining when considering thenth fractional dose, TD_(G) refers to the total dose goal, and FD refersto each fractional dose (with FD(1) representing the fractional doseassociated with a first fractional delivery, and FD(n−1) representingthe fractional dose associated with the fractional delivery just priorto the nth fractional dose.

As another useful example in these regards, this other, different doseobjective can comprise, at least in part, a predictive-dose objective.This objective represents a prediction for one or more individualdelivery fractions and/or an aggregation of one or more such deliveryfractions. As another useful example in these regards, this other,different dose objective can comprise, at least in part, apredictive-dose objective. This objective represents a prediction forone or more individual delivery fractions and/or an aggregation of oneor more such delivery fractions. By way of illustration, a total doselimit for the patient's spinal cord may be 40 Gy and the patient'sspinal cord may already have received 30 Gy's during the first tenfractions of a twenty-fraction treatment. These numbers could be used tocalculate that the patient is receiving 3 Gy per fraction. At this rate,the patient's spinal cord will receive a predicted total of 60 Gy duringthe complete treatment session and this will exceed the 40 Gy limit. Insuch a case this process can respond by working to minimize furtherdosing of the spinal cord (for example, by limiting future fractions tono more than 1 Gy).

Referring now to FIG. 2, another illustrative process 200 that iscompatible with many of these teachings will be presented. This process200 relates to facilitating the re-optimization of an existingradiation-treatment plan that has a corresponding resultant quality andthat is defined, at least in part, by at least one delivery parameter.This existing radiation-treatment plan can be the result of having usedthe process 100 described above or can be the result of any number ofother treatment-plan development methodologies as desired. This process200 can also be carried out by an appropriately configured controlcircuit as described below.

At step 201 this process 200 provides for specifying at least oneconstraint as regards the at least one delivery parameter as a function,at least in part, of the aforementioned resultant quality. Thisspecification activity can comprise, for example, setting the at leastone constraint to correspond to at least one setting as comprises a partof that existing radiation-treatment plan. In effect, this can compriseseeking to assure that the delivered dose is acceptably close to thecalculated dose. The latter can be important because the dose calculatedin the planning phase is used for evaluating the quality of thetreatment overall. One example of a quality metric used in suchcomparisons is referred to as gamma evaluation where the acceptancecriteria is typically 95 percent of points that are within 3 percent ofthe dose level and within a distance of 3.0 millimeters.

The aforementioned delivery parameter can vary with the needs and/oropportunities as tend to characterize a given application setting. Byone approach, for example, the delivery parameter can pertain tofluence. Fluence, of course, represents radiative flux integrated overtime and comprises a fundamental metric in dosimetry (i.e., themeasurement and calculation of an absorbed dose of ionizing radiation inmatter and tissue). In this case, the constraint as regards the deliveryparameter can comprise a maximum or minimum fluence to be applied to atarget, adjacent tissue, a specific organ, and so forth.

By another approach, in lieu of the foregoing or in combinationtherewith, the delivery parameter can pertain to some or all of themechanical settings of a radiation-delivery apparatus. FIG. 3illustrates some non-limiting examples in these regards. The mechanicalsetting or settings of interest can pertain, for example, to a patientsupport platform 301 (such as a couch). In such a case the mechanicalsetting can comprise, for example, vertical positioning 302 of thepatient support platform 301, horizontal positioning 303 of the patientsupport platform 301, longitudinal positioning 304 of the patientsupport platform 301, and/or rotational positioning 304 of the patientsupport platform 301 at various times during the radiation-treatmentsession (such as, for example, during one or more delivery fractions).Other patient support platform positions can be accommodated as well asdesired such as an angle of inclination of part or all of the patientsupport platform 301.

Other mechanical settings can pertain to one or more collimators ascomprise a part of the radiation-delivery apparatus 300. A singlemulti-leaf collimator 306 serves as an illustrative example in theseregards but it will be understood that other types and/or numbers ofcollimators can be readily accommodated in these same regards. In such acase, the mechanical setting(s) can comprise a collimator position (suchas a side-to-side position 307 or an inward-or-outward position 308), acollimator angle 309, and/or one or more multi-leaf collimator leafposition settings. (Multi-leaf collimators are comprised of a pluralityof individual parts (known as “leaves”) that are formed of a high atomicnumbered material (such as tungsten) that can move independently in andout of the path of the radiation-therapy beam in order to selectivelyblock (and hence shape) the beam. A radiation-treatment plan thatpresumes use of such a collimator will typically account for theposition of each such leaf.)

And as yet another illustrative example in these regards, the mechanicalsetting can pertain to the specification location/orientation of one ormore radiation sources 310 and/or the dose-administration rate 311. Thedose-administration rate 311 can comprise, for example, the amount ofenergy over time that the apparatus 300 administers to the patient.

Referring again to FIG. 2, at step 202 this process 200 provides forapplying the at least one constraint when re-optimizing the existingradiation-treatment plan to thereby facilitate at least substantiallymaintaining the resultant quality while nevertheless changing theexisting radiation-treatment plan. By one approach, for example, thisstep 202 can comprise using that constraint to limit search space whenre-optimizing the existing radiation-treatment plan. This mightcomprise, for example, limiting an allowed amount of change in fluenceor multi-leaf collimator leaf movement. As another example for anoptimization that can affect a gantry angle, collimator angle, orcouch-rotation angle, this can comprise limiting changes to thoserotation angles.

By another approach, in lieu of the foregoing or in combinationtherewith, this step 202 can comprise using the constraint to assess adistance between the existing radiation-treatment plan and at least onecandidate re-optimized radiation-treatment plan. When, for example, thatdistance exceeds the specified constraint (either at all or in somesuitably continuous and persistent manner as desired) the candidatere-optimized radiation-treatment plan can be discarded even if thatre-optimized plan otherwise appears better than the existing plan insome other way or view.

The above-described processes 100 and 200 are readily enabled using anyof a wide variety of available and/or readily configured platforms,including partially or wholly-programmable platforms as are known in theart or dedicated-purpose platforms as may be desired for someapplications. Referring now to FIG. 4, an illustrative approach to sucha platform will now be provided.

In this illustrative the apparatus 400 comprises a control circuit 401.Such a control circuit 401 can comprise a fixed-purpose hard-wiredplatform or can comprise a partially or wholly-programmable platform.All of these architectural options are well known and understood in theart and require no further description here. This control circuit 401 isconfigured (for example, by using corresponding programming as will bewell understood by those skilled in the art) to carry out one or more ofthe steps, actions, and/or functions described herein.

This control circuit 401 can operably couple to an optional memory 402that may be integral to the control circuit 401 or can be physicallydiscrete (in whole or in part) from the control circuit 401 as desired.This memory 402 can serve, for example, to non-transitorily store thecomputer instructions that, when executed by the control circuit 401,cause the control circuit 401 to behave as described herein. (As usedherein, this reference to “non-transitorily” will be understood to referto a non-ephemeral state for the stored contents (and hence excludeswhen the stored contents merely constitute signals or waves) rather thanvolatility of the storage media itself and hence includes bothnon-volatile memory (such as read-only memory (ROM) as well as volatilememory (such as an erasable programmable read-only memory (EPROM).)

Depending upon the application setting this control circuit 401 can alsooperably couple to an optional user interface 403 and/or an optionalnetwork interface 404. The user interface 403 can comprise any of avariety of mechanisms to permit a user to enter data, selections,instructions, and so forth and/or to provide information to the user.Examples in these regards include, but are not limited to, keyboards andkeypads, real and virtual buttons and switches, cursor control devices,displays of various kinds including touch-screen displays,voice-recognition components, printers, text-to-speech components, andso forth. The network interface 404, in turn, can comprise any of avariety of wireless and non-wireless interfaces to permit the controlcircuit 401 to access other resources via one or more interveningcommunication networks. These teachings are not particularly sensitiveto any particular choices made in these regards; accordingly, furtherelaboration in these regards will not be provided here for the sake ofbrevity.

So configured, a radiation-treatment plan can be optimized and/orre-optimized in ways that achieve superior results in at least someapplication settings and/or that achieve satisfactory results using lesstime and/or computational resources. These teachings are useful for awide variety of radiation-treatment modalities including numerousexisting approaches.

Those skilled in the art will recognize that a wide variety ofmodifications, alterations, and combinations can be made with respect tothe above described embodiments without departing from the spirit andscope of the invention, and that such modifications, alterations, andcombinations are to be viewed as being within the ambit of the inventiveconcept.

We claim:
 1. A method to facilitate re-optimizing an existingradiation-treatment plan having a corresponding resultant quality anddefined, at least in part, by at least one delivery parameter, themethod comprising: by a control circuit: specifying at least oneconstraint as regards the at least one delivery parameter as a function,at least in part, of the resultant quality; applying the at least oneconstraint when re-optimizing the existing radiation-treatment plan tothereby facilitate at least substantially maintaining the resultantquality while nevertheless changing the existing radiation-treatmentplan.
 2. The method of claim 1 wherein the at least one deliveryparameter pertains to fluence.
 3. The method of claim 1 wherein the atleast one delivery parameter pertains to mechanical settings of aradiation-delivery apparatus.
 4. The method of claim 3 wherein themechanical settings comprise at least one of the group consisting of:collimator angle; collimator position; patient support;dose-administration rates.
 5. The method of claim 3 wherein themechanical settings comprise multi-leaf collimator leaf positionsettings.
 6. The method of claim 1 wherein specifying at least oneconstraint as regards the at least one delivery parameter comprises, atleast in part, setting the at least one constraint to correspond to atleast one setting as comprises a part of the existingradiation-treatment plan.
 7. The method of claim 1 wherein applying theat least one constraint when re-optimizing the existingradiation-treatment plan comprises using the at least one constraint tolimit search space when re-optimizing the existing radiation-treatmentplan.
 8. The method of claim 1 wherein applying the at least oneconstraint when re-optimizing the existing radiation-treatment plancomprises using the at least one constraint to assess a distance betweenthe existing radiation-treatment plan and at least one candidatere-optimized radiation-treatment plan.
 9. An apparatus to facilitatere-optimizing an existing radiation-treatment plan having acorresponding resultant quality and defined, at least in part, by atleast one delivery parameter, the apparatus comprising: a controlcircuit configured to: specify at least one constraint as regards the atleast one delivery parameter as a function, at least in part, of theresultant quality; and apply the at least one constraint whenre-optimizing the existing radiation-treatment plan to therebyfacilitate at least substantially maintaining the resultant qualitywhile nevertheless changing the existing radiation-treatment plan. 10.The apparatus of claim 9 wherein the at least one delivery parameterpertains to fluence.
 11. The apparatus of claim 9 wherein the at leastone delivery parameter pertains to mechanical settings of aradiation-delivery apparatus.
 12. The apparatus of claim 11 wherein themechanical settings comprise at least one of the group consisting of:collimator angle; collimator position; patient support;dose-administration rates.
 13. The apparatus of claim 11 wherein themechanical settings comprise multi-leaf collimator leaf positionsettings.
 14. The apparatus of claim 9 wherein the control circuit isconfigured to specify at least one constraint as regards the at leastone delivery parameter by, at least in part, setting the at least oneconstraint to correspond to at least one setting as comprises a part ofthe existing radiation-treatment plan.
 15. The apparatus of claim 9wherein the control circuit is configured to apply the at least oneconstraint when re-optimizing the existing radiation-treatment plan byusing the at least one constraint to limit search space whenre-optimizing the existing radiation-treatment plan.
 16. The apparatusof claim 9 wherein the control circuit is configured to apply the atleast one constraint when re-optimizing the existing radiation-treatmentplan by using the at least one constraint to assess a distance betweenthe existing radiation-treatment plan and at least one candidatere-optimized radiation-treatment plan.